GPU packet classification using OpenCL: a consideration of viable classification methods
Department of Computer Science, Rhodes University, Grahamstown, South Africa
In SAICSIT ’09: Proceedings of the 2009 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists (2009), pp. 160-169.
@conference{nottingham2009gpu,
title={GPU packet classification using OpenCL: a consideration of viable classification methods},
author={Nottingham, A. and Irwin, B.},
booktitle={Proceedings of the 2009 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists},
pages={160–169},
year={2009},
organization={ACM}
}
Packet analysis is an important aspect of network security, which typically relies on a flexible packet filtering system to extrapolate important packet information from each processed packet. Packet analysis is a computationally intensive, highly parallelisable task, and as such, classification of large packet sets, such as those collected by a network telescope, can require significant processing time. We wish to improve upon this, through parallel classification on a GPU. In this paper, we first consider the OpenCL architecture and its applicability to packet analysis. We then introduce a number of packet demultiplexing and routing algorithms, and finally present a discussion on how some of these techniques may be leveraged within a GPGPU context to improve packet classification speeds.
October 28, 2010 by hgpu
